Bioinformatics. 2018 Sep 1;34(17):2881-2888. doi: 10.1093/bioinformatics/bty198.
Software pipelines have become almost standardized tools for microbiome analysis. Currently many pipelines are available, often sharing some of the same algorithms as stages. This is largely because each pipeline has its own source language and file formats, making it typically more economical to reinvent the wheel than to learn and interface to an existing package. We present Plugin-Based Microbiome Analysis (PluMA), which addresses this problem by providing a lightweight back end that can be infinitely extended using dynamically loaded plugin extensions. These can be written in one of many compiled or scripting languages. With PluMA and its online plugin pool, algorithm designers can easily plug-and-play existing pipeline stages with no knowledge of their underlying implementation, allowing them to efficiently test a new algorithm alongside these stages or combine them in a new and creative way.
We demonstrate the usefulness of PluMA through an example pipeline (P-M16S) that expands an obesity study involving gut microbiome samples from the mouse, by integrating multiple plugins using a variety of source languages and file formats, and producing new results.
Links to github repositories for the PluMA source code and P-M16S, in addition to the plugin pool are available from the Bioinformatics Research Group (BioRG) at: http://biorg.cis.fiu.edu/pluma.
软件管道已成为微生物组分析的几乎标准化工具。目前有许多管道可用，它们通常共享一些相同的算法作为阶段。这在很大程度上是因为每个管道都有自己的源语言和文件格式，因此重新发明轮子通常比学习和接口到现有软件包更经济。我们提出了基于插件的微生物组分析 (PluMA)，通过提供一个轻量级的后端来解决这个问题，该后端可以使用动态加载的插件扩展无限扩展。这些插件可以用多种编译或脚本语言编写。使用 PluMA 和其在线插件池，算法设计者可以轻松地即插即用现有的管道阶段，而无需了解其底层实现，从而使他们能够在这些阶段旁边高效地测试新算法，或者以新的创造性方式组合它们。
我们通过一个示例管道 (P-M16S) 展示了 PluMA 的有用性，该管道通过使用多种源语言和文件格式集成多个插件来扩展涉及来自小鼠的肠道微生物组样本的肥胖研究，并产生新的结果。
PluMA 的源代码和 P-M16S 的 github 存储库以及插件池的链接可从位于：http://biorg.cis.fiu.edu/pluma 的生物信息学研究组 (BioRG) 获得。
